---
title: "The History of Airplane Crashes"
output: 
  flexdashboard::flex_dashboard:
    theme: 
      version: 4
      bootswatch: flatly
      primary: "#DCA30B"
      secondary: "#000000"
    orientation: columns
    vertical_layout: fill
    source_code: embed
---
<style type="text/css">
.chart-title {  /* chart_title  */
    font-size: 16px;
  }
body{ /* Normal */
      font_size: 16px
        }
</style>

```{r setup, include=FALSE}
library(flexdashboard)
library(readr)
library(tidyverse)
library(conflicted)
library(stringi)
library(plotly)
conflict_prefer("select", "dplyr")
conflict_prefer("filter", "dplyr")
crashes <- read_csv("crashes.csv")
crashef <- read_csv("crashes.csv")
```

Overview 
===

Column {.tabset data-width=1000}
---

### The Data

```{r Data_Edits}
crashes <- crashes[,-c(8, 9)]

test <- str_remove_all(crashes$Date, c(" ")) 

test <- str_remove_all(test, c(",")) 

crashes$Month <- substr(test,1,nchar(test)-6)

crashes$Year <- stri_extract_last_regex(crashes$Date, "\\d{4}")

crashes$Location <- str_remove(crashes$Location, "Near")

crashes$Location <- str_remove(crashes$Location, "Off")

crashes$Mortality <- (crashes$`Total Fatalities`/crashes$`Total Aboard`)



crashes <- crashes%>%
  mutate(
    Eras = case_when(
    Year >= 1903 & Year < 1919 ~ "Pioneer",
    Year >= 1919 & Year < 1946 ~ "Golden Age",
    Year >= 1946 & Year < 1980 ~ "Post War",
    Year >= 1980 & Year < 2001 ~ "Digital",
    Year >= 2001 ~ "21st Century"),
    Eras = factor(Eras, level = c("Pioneer", "Golden Age", "Post War", "Digital", "21st Century")))

crash <- crashes %>% select(Year, Month, Date, Eras, everything())

crash <- separate(crash, Location, into = c("City", "Country"), sep = ", ")

crash$Country <- ifelse(crash$Country %in% state.name, "United States", crash$Country)

crash$Month <- factor(crash$Month, 
                   levels = c("January", "February", "March", "April", "May", "June",
                              "July", "August", "September", "October", "November", "December"))
```

**About the Data**

The data used in this project is about all recorded plane crashes in world history. From the First ever recorded plane crash in 1908 up until the end of March 2020. In this data set I have divided up all of the data into 5 eras(Pioneer, Golden Age, Postwar, Digital and 21st Century) and these are commonly known in the aviation community(except for the 21st Century because technically were still in the digital era, but i didnt want to have an "era" to have 40 years worth of data). During this slide show, you will be guided through these eras and theyre crashes, but I will also be including major feets of these eras so you can understand how far we are in the development of airplanes.

```{r Table}
crash <- crash[,-c(19)]
index <- sample(1:nrow(crash), 100)
result <- crash[index,]

DT::datatable(result)

```


### Which Era Has the Most Crashes?

```{r}
p1 <- ggplot(crash, aes(x = Eras)) + 
  geom_bar(fill="#DCA30B", alpha=.6, width=.4) + 
  coord_flip() +
  theme(text = element_text(size = 20))
ggplotly(p1)

```


### Which Era Saw the Most Fatalities by Year?

```{r Fatal Boxplot}
crash$Year <- as.integer(crash$Year)

p4 <- ggplot(data = crash, mapping = aes(x = Year, y = `Total Fatalities`)) +
    geom_point(alpha = 0.3, aes(color = Eras))
ggplotly(p4)
```



Pioneer Era 
===

Column {.tabset data-width=1000}
---

### Pioneer Era Data (1903-1918) 

**About This Era**

1903 was the birth year of the present day Airplanes, many were attempted before this but the Wright Brother's were the first powered and controlled flight. They didnt start officially start recording crashes up until 1908, by this time the first powered and controlled flights in Europe and New Zealand were successful. The first reported airplane crash was in Fort Myer, Virginia in 1908.The plane was operated by Orville Wright and was showing off the plane with Lt. Thomas Selfridge on board as a passenger. During the flight the plane fell into a nose dive from 75 feet and crashed into the ground killing Lt. Thomas Selfridge. This was the first known death from flying in an airplane. This Era ends in 1918 at the end of World War 1 when people started to see the potential in airplanes in war and more people started to create new and improved ways of flying.

```{r datatable}
pio <- filter(crash, Eras == "Pioneer")

DT::datatable(head(pio, 24))
```


### Era Specific Statistics


```{r Pio Stats}
pio$Year <- as.factor(pio$Year)
p2 <- ggplot(pio, aes(x=Year, y=`Total Fatalities`, size = Mortality)) +
    geom_point(color="#DCA30B") +
    theme_bw() 
ggplotly(p2)

```

### Pioneer Operator Statistics

```{r PioOpstats1}
pioplt <- ggplot(pio) +
  geom_hline(
    aes(yintercept = y), 
    data.frame(y = c(0:2) * 12.5),
    color = "lightgrey"
  ) + 
  geom_col(
    aes(
      x = reorder(str_wrap(Operator, 5), `Total Fatalities`),
      y = `Total Fatalities`,
      fill = `Total Fatalities`
    ),
    position = "dodge2",
    show.legend = TRUE,
    alpha = .9
  ) + 
  coord_polar()

pioplt

```



Golden Age 
===

Column {.tabset data-width=1000}
---

### Golden Age Data (1919-1945)

*About This Era*

In the Golden Age, there were many significant events and developments that happened. Some of the most notable events and developments include: The end of World War I, which saw the widespread use of aircraft in warfare and led to rapid advancements in aviation technology. The establishment of the first commercial airlines, such as KLM and British Airways, which began offering regular passenger flights. The development of new aircraft designs, such as the Boeing 247 and Douglas DC-3, which were more reliable and comfortable than previous models. The expansion of air travel to long-distance routes, such as transatlantic flights, which made air travel more accessible to the general public. The advent of air mail service, which greatly improved communication and made it possible to send letters and packages quickly around the world. The start of World War II, which saw the widespread use of aircraft in warfare and led to further advancements in aviation technology, such as jet engines and advanced weapons systems.

```{r GE}
ga <- filter(crash, crash[,4] == "Golden Age")

DT::datatable(head(ga, 15))
```

Postwar Era 
===

Column {.tabset data-width=1000}
---

### Postwar Era Data

*About this Era*

In the Postwar Era, there were many significant events and developments. Some of the most notable events and developments include: The development of the first successful commercial jet airliner, the de Havilland Comet, which entered service in 1952. The launch of the first satellite, Sputnik 1, by the Soviet Union in 1957, which paved the way for the development of satellite-based navigation systems. The development of supersonic aircraft, such as the Concorde, which entered service in 1976 and allowed for transatlantic travel at speeds of over twice the speed of sound. The construction of the first transcontinental interstate highway system in the United States, which greatly increased the ease and speed of air travel within the country. The growth of the global airline industry, as more and more people began to travel by air for both business and leisure. The introduction of new safety regulations and technologies, such as the black box flight recorder and the use of radar for air traffic control, which greatly improved the safety of air travel.

```{r pwe}
pw <- filter(crash, crash[,4] == "Post War")

DT::datatable(head(pw, 15))
```


### Crashes in this Era

```{r pwmap}


ggplot(pw, aes(x = Mortality, y = `Total Aboard`, color = `Total Fatalities`)) +
  geom_point() + 
  geom_smooth(se = TRUE) +
  theme(text = element_text(size = 15))

```

### Crash Data By Month

```{r pwmonth}
p6 <- ggplot(pw, aes(x = Month)) + geom_bar(fill="#DCA30B", width=.6) + coord_flip() +
  theme(text = element_text(size = 8))
ggplotly(p6)

pwplt <- ggplot(pw) +
  geom_col(aes(`Total Fatalities`, Month), fill = "lightblue", width = 0.6) + theme(text = element_text(size = 8))
ggplotly(pwplt)
```






### Popular Crashes (Marshall Football)

```{r PCm}

Marshall <- filter(crashes, crashes[,1] == "November 14, 1970")



DT::datatable(head(Marshall,1))
```

### Popular Crashes (2 Plane Crash)

```{r PC2}
Double_Plane_Crash <- filter(crashes, crashes[,1] == "June 30, 1956")

DT::datatable(head(Double_Plane_Crash, 4, 6, 8, 12, 15))
```



Digital Era 
===

Column {.tabset data-width=1000}
---

### Digital Era Data (1980-2000)

*About this Era*

In the Digital Era we saw the development of more advanced and efficient commercial jet airliners, such as the Boeing 767 and Airbus A320, which greatly increased the capacity and range of air travel. The growth of low-cost carriers, such as Southwest Airlines and Ryanair, which made air travel more affordable and accessible to the general public. The expansion of global airline networks, as more and more airlines began offering flights to destinations around the world. The development of satellite-based navigation systems, such as the Global Positioning System (GPS), which greatly improved the safety and efficiency of air travel. The emergence of new technologies, such as the use of composite materials in aircraft construction and the development of fly-by-wire control systems, which greatly improved the performance and safety of aircraft.



```{r de}
de <- filter(crash, crash[,4] == "Digital")

DT::datatable(head(de, 15))
```


### On Board Crash Data

```{r CD}
p5 <- ggplot(data = de, aes(x = Year, y = `Total Aboard`)) +
    geom_line() +
    facet_wrap(facets = vars(Month))

ggplotly(p5)

```



### 




21st Century 
===

Column {.tabset data-width=1000}
---

### 21st Century Data

*About this Era*

Since the start of the 21st century we have seen, the continued growth of the global airline industry, with more and more people traveling by air for both business and leisure. The development of more advanced and efficient commercial jet airliners, such as the Boeing 787 Dreamliner and Airbus A350, which have improved fuel efficiency and passenger comfort. The emergence of new technologies, such as electric and hybrid-electric propulsion systems and the use of 3D printing in aircraft manufacturing, which are expected to greatly improve the sustainability and efficiency of air travel. The rise of space tourism, with companies such as Virgin Galactic and Blue Origin offering suborbital flights to paying customers.


```{r 21c}
twrst <- filter(crash, crash[,4] == "21st Century")

DT::datatable(head(twrst, 15))
```


About the Author
===



![](Download.jpg){width=50% height=50%}